A1 Refereed original research article in a scientific journal
Neurobiologically Based Stratification of Recent- Onset Depression and Psychosis: Identification of Two Distinct Transdiagnostic Phenotypes
Authors: Lalousis Paris Alexandros, Schmaal Lianne, Wood Stephen J., Reniers Renate L.E.P., Barnes Nicholas M., Chisholm Katharine, Griffiths Sian Lowri, Stainton Alexandra, Wen Junhao, Hwang Gyujoon, Davatzikos Christos, Wenzel Julian, Kambeitz-Ilankovic Lana, Andreou Christina, Bonivento Carolina, Dannlowski Udo, Ferro Adele, Lichtenstein Theresa, Riecher-Rössler Anita, Romer Georg, Rosen Marlene, Bertolino Alessandro, Borgwardt Stefan, Brambilla Paolo, Kambeitz Joseph, Lencer Rebekka, Pantelis Christos, Ruhrmann Stephan, Salokangas Raimo K.R., Schultze-Lutter Frauke, Schmidt André, Meisenzahl Eva, Koutsouleris Nikolaos, Dwyer Dominic, Upthegrove Rachel
Publisher: ELSEVIER SCIENCE INC
Publication year: 2022
Journal: Biological Psychiatry
Journal name in source: BIOLOGICAL PSYCHIATRY
Journal acronym: BIOL PSYCHIAT
Volume: 92
Issue: 7
First page : 552
Last page: 562
Number of pages: 11
ISSN: 0006-3223
eISSN: 1873-2402
DOI: https://doi.org/10.1016/j.biopsych.2022.03.021
Web address : https://www.sciencedirect.com/science/article/pii/S0006322322011568?via%3Dihub
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/178075911
BACKGROUND:
Identifying neurobiologically based transdiagnostic categories of depression and psychosis may elucidate heterogeneity and provide better candidates for predictive modeling. We aimed to identify clusters across patients with recent-onset depression (ROD) and recent-onset psychosis (ROP) based on structural neuroimaging data. We hypothesized that these transdiagnostic clusters would identify patients with poor outcome and allow more accurate prediction of symptomatic remission than traditional diagnostic structures.
METHODS:
HYDRA (Heterogeneity through Discriminant Analysis) was trained on whole-brain volumetric measures from 577 participants from the discovery sample of the multisite PRONIA study to identify neurobiologically driven clusters, which were then externally validated in the PRONIA replication sample (n = 404) and three datasets of chronic samples (Centre for Biomedical Research Excellence, n = 146; Mind Clinical Imaging Consortium, n = 202; Munich, n = 470).
RESULTS:
The optimal clustering solution was two transdiagnostic clusters (cluster 1: n = 153, 67 ROP, 86 ROD; cluster 2: n = 149, 88 ROP, 61 ROD; adjusted Rand index = 0.618). The two clusters contained both patients with ROP and patients with ROD. One cluster had widespread gray matter volume deficits and more positive, negative, and functional deficits (impaired cluster), and one cluster revealed a more preserved neuroanatomical signature and more core depressive symptomatology (preserved cluster). The clustering solution was internally and externally validated and assessed for clinical utility in predicting 9-month symptomatic remission, outperforming traditional diagnostic structures.
CONCLUSIONS:
We identified two transdiagnostic neuroanatomically informed clusters that are clinically and bio-logically distinct, challenging current diagnostic boundaries in recent-onset mental health disorders. These results may aid understanding of the etiology of poor outcome patients transdiagnostically and improve development of stratified treatments.
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